A slightly (I think?) different slant on why EA elitism bias/​top-university focus/​lack of diversity is a problem

Key point: People who come from different infrastructure/​geography/​etc. will often come up with different solutions, identify different problems, and predict certain issues more accurately.

Example #1 - Different solutions/​developed aptitudes: I’m friends with a bunch of people doing medical residencies in the US right now. The ones at top-tier hospitals are learning, mostly, how to provide great patient care. The ones at the lower-ranked hospitals are learning things like: (1) How to navigate bureaucracy, (2) How to advocate for their patients, and (3) Where the flaws in the US medical system are.

Basically, the ones at the lower-ranked hospitals now have many more ideas about what needs to be improved in our healthcare system. To connect this to EA: People with elite backgrounds are often less likely to know where certain (HUGE) problems are (because they are not repeatedly exposed to them) and to have much less experience/​detailed knowledge with regards to navigating them.

Example #2 - Accuracy/​Predictions: I’m from the US midwest. We all knew Trump was going to win in 2016, or at least that he had a good shot of winning. (Personally, I think this was because more people in the midwest regularly talks to farmer/​rural relatives or people who have them, but that’s not super relevant to this post). Not only were people on the coasts generally shocked, but the media reported that everyone was shocked.

Not everyone was shocked. Millions of Americans were not shocked. It was pretty much only the “elite” Americans who were shocked.

--> If EA remains elite-heavy, our predictions are gonna be wayyyyy (and avoidably) dumb a lot of the time.

Example #3 - Maybe skip this and go to example #4 if you found the previous two examples convincing

I went to an Ivy League university. My best friends went to state schools. They are now very good at navigating bureaucracy. I am very good at believing bureaucracy should be improved (because I’ve seen decent versions!) and also believing all the red tape doesn’t apply to me (sometimes it doesn’t! though it does seem to apply to most people! and my experience then gives me an incorrect idea of how systems actually function on average!).

Often, I cannot actually ignore red tape and am inefficient at getting through it. I need to team up with people who are.

(Also, my friends who went to state schools are roughly all as analytically intelligent as I am, etc., etc., but that point has been made in these forums a lot).

Example #4 - We’re really good at understanding this in things like public health: We totally understand (I think) that in a public health intervention we should do things like talk to the people the intervention is for so as to understand goals/​context/​solutions they’ve already figured out. Given that the goal of EA is to maximize pretty much everything for everyone (and in the future), we should be prioritizing including people from a very wide range of contexts.

(And people from the future, once we can figure that out).

Conclusion

This is another set of reasons why, at this point in the history of EA, we should continue to expand to a diversity of schools/​geographies/​etc: Our solutions will be better, we’ll identify problem areas more effectively, and our predictions will be more accurate.